Processing of Sensory Information by a Network of Oscillators with Memory

We propose a model of coupled oscillators with noise that performs binding and segmentation of objects using a set of stored images each consisting of figures and a background. The amplitudes of the oscillators encode the spatial and featural distribution of the external stimulus. In the learning stage the couplings between the phases are modified in a Hebb-like manner. By meanfield analysis and simulations we show that an external stimulus whose local features resemble those of one or several of the stored figures causes a selective phase coherence that retrieves the stored pattern of segmentation.

Authors: Tsodyks M., Sompolinsky H.
Year of publication: 1992
Journal: International Journal of Neural SystemsVol. 03, No. supp01, pp. 51-56 (1992)

Link to publication:


“Working memory”